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   Articles with "unsupervised deep" as a keyword



Unsupervised deep neuron-per-neuron hashing

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recommendations! Published in 2018 at "Applied Intelligence"

DOI: 10.1007/s10489-018-1353-5

Abstract: Hashing has been widely applied to approximate nearest neighbor search for large-scale multimedia retrieval. A variety of hashing methods have been developed for learning an efficient binary data representation, mainly by relaxing some imposed constraints… read more here.

Keywords: neuron; neuron hashing; deep neuron; unsupervised deep ... See more keywords

Unsupervised deep learning identifies semantic disentanglement in single inferotemporal face patch neurons

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recommendations! Published in 2021 at "Nature Communications"

DOI: 10.1038/s41467-021-26751-5

Abstract: In order to better understand how the brain perceives faces, it is important to know what objective drives learning in the ventral visual stream. To answer this question, we model neural responses to faces in… read more here.

Keywords: identifies semantic; deep learning; face; learning identifies ... See more keywords

Unsupervised deep denoising for four-dimensional scanning transmission electron microscopy

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recommendations! Published in 2024 at "npj Computational Materials"

DOI: 10.1038/s41524-024-01428-x

Abstract: By simultaneously achieving high spatial and angular sampling resolution, four dimensional scanning transmission electron microscopy (4D STEM) is enabling analysis techniques that provide great insight into the atomic structure of materials. Applying these techniques to… read more here.

Keywords: dimensional scanning; electron microscopy; transmission electron; scanning transmission ... See more keywords

High-throughput cryo-ET structural pattern mining by unsupervised deep iterative subtomogram clustering.

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recommendations! Published in 2023 at "Proceedings of the National Academy of Sciences of the United States of America"

DOI: 10.1073/pnas.2213149120

Abstract: Cryoelectron tomography directly visualizes heterogeneous macromolecular structures in their native and complex cellular environments. However, existing computer-assisted structure sorting approaches are low throughput or inherently limited due to their dependency on available templates and manual… read more here.

Keywords: iterative subtomogram; unsupervised deep; deep iterative; high throughput ... See more keywords

Unsupervised Deep Learning Can Identify Protein Functional Groups from Unaligned Sequences

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recommendations! Published in 2023 at "Genome Biology and Evolution"

DOI: 10.1093/gbe/evad084

Abstract: Abstract Interpreting protein function from sequence data is a fundamental goal of bioinformatics. However, our current understanding of protein diversity is bottlenecked by the fact that most proteins have only been functionally validated in model… read more here.

Keywords: unsupervised deep; learning identify; learning; deep learning ... See more keywords

Characterizing and Clustering Debris Flow and Environmental Noise Seismic Signals Using Unsupervised Deep Learning

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recommendations! Published in 2025 at "Geophysical Journal International"

DOI: 10.1093/gji/ggaf353

Abstract: Debris flows pose a significant threat to the sustainable development of mountainous regions. As an effective real-time sensing technique, microseismic monitoring plays a critical role in the detection and analysis of debris flow activity. However,… read more here.

Keywords: environmental noise; debris; debris flow; flow events ... See more keywords

Unsupervised Deep Learning to Detect Agitation from Videos in People with Dementia

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recommendations! Published in 2023 at "IEEE Access"

DOI: 10.1109/access.2022.3143990

Abstract: Behavioural symptoms of dementia present a significant risk within Long Term Care (LTC) homes, which face difficulties supporting residents and monitoring their safety with limited staffing resources. Many LTC facilities have installed video surveillance systems… read more here.

Keywords: detect agitation; unsupervised deep; people dementia; deep learning ... See more keywords

Unsupervised Deep-Learning-Based Reconfigurable Intelligent Surface-Aided Broadcasting Communications in Industrial IoTs

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recommendations! Published in 2022 at "IEEE Internet of Things Journal"

DOI: 10.1109/jiot.2022.3169276

Abstract: This article presents a general system framework that lays the foundation for reconfigurable intelligent surface (RIS)-enhanced broadcast communications in Industrial Internet of Things (IIoTs). In our system model, we consider multiple sensor clusters co-existing in… read more here.

Keywords: unsupervised deep; intelligent surface; reconfigurable intelligent; deep learning ... See more keywords

Hybrid Beamforming Based on an Unsupervised Deep Learning Network for Downlink Channels With Imperfect CSI

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recommendations! Published in 2022 at "IEEE Wireless Communications Letters"

DOI: 10.1109/lwc.2022.3179362

Abstract: Hybrid beamforming can provide rapid data transmission rates while reducing the complexity and cost of massive multiple-input multiple-output (MIMO) systems. However, channel state information (CSI) is imperfect in realistic downlink channels, introducing challenges to hybrid… read more here.

Keywords: unsupervised deep; imperfect csi; deep learning; downlink channels ... See more keywords

Efficient Duplicate Comment Detection for Rulemaking Agencies With Unsupervised Deep Learning: A Cost-Effective and High-Accuracy Approach

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recommendations! Published in 2025 at "IEEE Transactions on Computational Social Systems"

DOI: 10.1109/tcss.2024.3522837

Abstract: Government agencies tasked with soliciting comments from the American public in response to changes in rulemaking have long been interested in finding effective techniques to automatically process spam comments, including flagging and filtering duplicate comments.… read more here.

Keywords: deep learning; duplicate comments; unsupervised deep; rulemaking agencies ... See more keywords

Unsupervised Deep Background Matting Using Deep Matte Prior

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recommendations! Published in 2022 at "IEEE Transactions on Circuits and Systems for Video Technology"

DOI: 10.1109/tcsvt.2021.3132461

Abstract: Background matting is a recently developed image matting approach, with applications to image and video editing. It refers to estimating both the alpha matte and foreground from a pair of images with and without foreground… read more here.

Keywords: deep matte; unsupervised deep; alpha matte; background matting ... See more keywords